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» Mining Frequent Itemsets Using Re-Usable Data Structure
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CORR
2008
Springer
114views Education» more  CORR 2008»
13 years 7 months ago
Dynamic index selection in data warehouses
Analytical queries defined on data warehouses are complex and use several join operations that are very costly, especially when run on very large data volumes. To improve response...
Stéphane Azefack, Kamel Aouiche, Jér...
KDD
2008
ACM
246views Data Mining» more  KDD 2008»
14 years 8 months ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
ACMSE
2008
ACM
13 years 9 months ago
Mining frequent sequential patterns with first-occurrence forests
In this paper, a new pattern-growth algorithm is presented to mine frequent sequential patterns using First-Occurrence Forests (FOF). This algorithm uses a simple list of pointers...
Erich Allen Peterson, Peiyi Tang
FIMI
2004
123views Data Mining» more  FIMI 2004»
13 years 9 months ago
Surprising Results of Trie-based FIM Algorithms
Trie is a popular data structure in frequent itemset mining (FIM) algorithms. It is memory-efficient, and allows fast construction and information retrieval. Many trie-related tec...
Ferenc Bodon
ICDE
2005
IEEE
118views Database» more  ICDE 2005»
14 years 9 months ago
Scrutinizing Frequent Pattern Discovery Performance
Benchmarking technical solutions is as important as the solutions themselves. Yet many fields still lack any type of rigorous evaluation. Performance benchmarking has always been ...
Mohammad El-Hajj, Osmar R. Zaïane, Stella Luk...